plot_forecast

---

method plot_forecast(models=None, fh="test", X=None, target=0, plot_interval=True, title=None, legend="upper left", figsize=(900, 600), filename=None, display=True)[source]

Plot a time series with model forecasts.

This plot is only available for forecasting tasks.

Parameters

models: int, str, Model, slice, sequence or None, default=None Models to plot. If None, all models are selected. If no models are selected, only the target column is plotted. fh: int, str, range, sequence or ForecastingHorizon, default="test" Forecast horizon for which to plot the predictions. If string, choose from: "train", "test" or "holdout". Use a sequence or add + between options to select more than one. X: dataframe-like or None, default=None Exogenous time series corresponding to fh. This parameter is ignored if fh is a data set. target: int or str, default=0 Target column to look at. Only for multivariate tasks. plot_interval: bool, default=True Whether to plot prediction intervals instead of the exact prediction values. If True, the plotted estimators should have a predict_interval method. title: str, dict or None, default=None Title for the plot. If None, no title is shown. If str, text for the title. If dict, title configuration. legend: str, dict or None, default="upper left" Legend for the plot. See the user guide for an extended description of the choices. If None: No legend is shown. If str: Location where to show the legend. If dict: Legend configuration. figsize: tuple, default=(900, 600) Figure's size in pixels, format as (x, y). filename: str or None, default=None Save the plot using this name. Use "auto" for automatic naming. The type of the file depends on the provided name (.html, .png, .pdf, etc...). If filename has no file type, the plot is saved as html. If None, the plot is not saved. display: bool or None, default=True Whether to render the plot. If None, it returns the figure.

Returns

go.Figure or None Plot object. Only returned if display=None.

See Also

plot_lift

Plot the lift curve.

plot_prc

Plot the precision-recall curve.

plot_roc

Plot the Receiver Operating Characteristics curve.

Example

>>> from atom import ATOMForecaster
>>> from sktime.datasets import load_airline

>>> y = load_airline()

>>> atom = ATOMForecaster(y, random_state=1)
>>> atom.plot_forecast()

>>> atom.run(
...     models="arima",
...     est_params={"order": (1, 1, 0), "seasonal_order": (0, 1, 0, 12)},
... )
>>> atom.plot_forecast()

>>> atom.plot_forecast(fh="train+test", plot_interval=False)

>>> # Forecast the next 4 years starting from the test set
>>> atom.plot_forecast(fh=range(1, 48))